Stock Image

Robust Knapsack

Simon Stelling

Published by AV Akademikerverlag
ISBN 10: 3639474198 / ISBN 13: 9783639474190
New / Paperback / Quantity Available: 20
From BuySomeBooks (Las Vegas, NV, U.S.A.)
Available From More Booksellers
View all  copies of this book
Add to basket
List Price: US$
Price: US$ 102.97
Convert Currency
Shipping: US$ 3.95
Within U.S.A.
Destination, Rates & Speeds

30 Day Returns Policy

Save for Later

About the Book

Bibliographic Details


Title: Robust Knapsack

Publisher: AV Akademikerverlag

Binding: Paperback

Book Condition: New

Book Type: Paperback

Description:

Paperback. 88 pages. Dimensions: 8.7in. x 5.9in. x 0.2in.We approach the knapsack problem from a statistical learning perspective. We consider a stochastic setting with uncertainty about the description of the problem instances. As a consequence, uncertainty about the optimal solution arises. We present a characterization of different classes of knapsack problem instances based on their sensitivity to noise variations. We do so by calculating the informativeness as measured by the approximation set coding (ASC) principle. We also demonstrate experimentally that, depending on the problem instance class, the ability to reliably localize good knapsack solution sets may or may not be a requirement for good generalization performance. Furthermore, we present a parametrization of knapsack solutions based on the concept of a knapsack core. We show that this parametrization allows to regularize the model complexity of the knapsack learning problem. Algorithms based on the core concept may benefit from this parametrization to achieve better generalization performance at reduced running times. Finally, we consider a randomized approximation scheme for the counting knapsack problem proposed by Dyer. We employ the ASC principle to determine the maximally informative approximation ratio. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Bookseller Inventory # 9783639474190

About this title:

Book ratings provided by GoodReads:
0 avg rating
(0 ratings)

Synopsis: We approach the knapsack problem from a statistical learning perspective. We consider a stochastic setting with uncertainty about the description of the problem instances. As a consequence, uncertainty about the optimal solution arises. We present a characterization of different classes of knapsack problem instances based on their sensitivity to noise variations. We do so by calculating the informativeness as measured by the approximation set coding (ASC) principle. We also demonstrate experimentally that, depending on the problem instance class, the ability to reliably localize good knapsack solution sets may or may not be a requirement for good generalization performance. Furthermore, we present a parametrization of knapsack solutions based on the concept of a knapsack core. We show that this parametrization allows to regularize the model complexity of the knapsack learning problem. Algorithms based on the core concept may benefit from this parametrization to achieve better generalization performance at reduced running times. Finally, we consider a randomized approximation scheme for the counting knapsack problem proposed by Dyer. We employ the ASC principle to determine the maximally informative approximation ratio.

About the Author: was 25 years old when he attained his master's degree in computer science at ETH Zürich. He currently works as a software engineer at Ergon Informatik.

"About this title" may belong to another edition of this title.

Bookseller & Payment Information

Payment Methods

This bookseller accepts the following methods of payment:

  • American Express
  • MasterCard
  • Visa

[Search this Seller's Books]

[List this Seller's Books]

[Ask Bookseller a Question]

Bookseller: BuySomeBooks
Address: Las Vegas, NV, U.S.A.

AbeBooks Bookseller Since: May 21, 2012
Bookseller Rating: 5-star rating

Terms of Sale:

We guarantee the condition of every book as it's described on the Abebooks web
sites. If you're dissatisfied with your purchase (Incorrect Book/Not as
Described/Damaged) or if the order hasn't arrived, you're eligible for a refund
within 30 days of the estimated delivery date. If you've changed your mind about a book that you've ordered, please use the Ask bookseller a question link to contact us and we'll respond within 2 business days.

BuySomeBooks is operated by Drive-On-In, Inc., a Nevada co...

[More Information]

Shipping Terms:

Orders usually ship within 1-2 business days. Books are shipped from multiple locations so your order may arrive from Las Vegas,NV, Roseburg,OR, La Vergne,TN, Momence,IL, or Commerce,GA.


Store Description: BuySomeBooks is great place to get your books online. With over eight million titles available we're sure to have what you're looking for. Despite having a large selection of new books available for immediate shipment and excellent customer service, people still tell us they prefer us because of our prices.